End of training

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3751
-- Accuracy: 0.8853
-- Precision: 0.8785
-- Recall: 0.8773
-- F1: 0.8773
+- Loss: 0.3660
+- Accuracy: 0.8991
+- Precision: 0.8990
+- Recall: 0.8942
+- F1: 0.8959
 
 ## Model description
 
@@ -44,32 +44,27 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- num_epochs: 15
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 1.3635        | 1.0   | 48   | 1.1593          | 0.5963   | 0.4671    | 0.5259 | 0.4501 |
-| 0.9895        | 2.0   | 96   | 0.7987          | 0.6881   | 0.6824    | 0.6271 | 0.6017 |
-| 0.6845        | 3.0   | 144  | 0.6432          | 0.7523   | 0.7789    | 0.7076 | 0.7071 |
-| 0.5856        | 4.0   | 192  | 0.5896          | 0.7844   | 0.8315    | 0.7457 | 0.7463 |
-| 0.4328        | 5.0   | 240  | 0.4232          | 0.8716   | 0.8750    | 0.8585 | 0.8645 |
-| 0.4298        | 6.0   | 288  | 0.4118          | 0.8853   | 0.8783    | 0.8810 | 0.8789 |
-| 0.322         | 7.0   | 336  | 0.3988          | 0.8807   | 0.8824    | 0.8655 | 0.8712 |
-| 0.3561        | 8.0   | 384  | 0.4169          | 0.8716   | 0.8630    | 0.8679 | 0.8637 |
-| 0.27          | 9.0   | 432  | 0.3779          | 0.8991   | 0.8972    | 0.8913 | 0.8938 |
-| 0.2472        | 10.0  | 480  | 0.3850          | 0.8991   | 0.8928    | 0.8942 | 0.8924 |
-| 0.2349        | 11.0  | 528  | 0.3749          | 0.8945   | 0.8855    | 0.8919 | 0.8875 |
-| 0.2491        | 12.0  | 576  | 0.3798          | 0.9037   | 0.8969    | 0.8992 | 0.8975 |
-| 0.2239        | 13.0  | 624  | 0.3778          | 0.8853   | 0.8783    | 0.8810 | 0.8793 |
-| 0.2276        | 14.0  | 672  | 0.3755          | 0.8899   | 0.8827    | 0.8823 | 0.8822 |
-| 0.206         | 15.0  | 720  | 0.3751          | 0.8853   | 0.8785    | 0.8773 | 0.8773 |
+| 0.3839        | 1.0   | 24   | 0.4077          | 0.8716   | 0.8635    | 0.8717 | 0.8639 |
+| 0.3268        | 2.0   | 48   | 0.4052          | 0.8578   | 0.8510    | 0.8489 | 0.8467 |
+| 0.2524        | 3.0   | 72   | 0.4014          | 0.8899   | 0.8938    | 0.8795 | 0.8843 |
+| 0.2171        | 4.0   | 96   | 0.3582          | 0.8899   | 0.8860    | 0.8849 | 0.8846 |
+| 0.1712        | 5.0   | 120  | 0.3983          | 0.8899   | 0.8885    | 0.8804 | 0.8826 |
+| 0.1627        | 6.0   | 144  | 0.3789          | 0.8991   | 0.8984    | 0.8998 | 0.8983 |
+| 0.1462        | 7.0   | 168  | 0.3884          | 0.8991   | 0.9004    | 0.8922 | 0.8955 |
+| 0.1499        | 8.0   | 192  | 0.3727          | 0.9083   | 0.9069    | 0.9080 | 0.9070 |
+| 0.1557        | 9.0   | 216  | 0.3669          | 0.8991   | 0.8990    | 0.8942 | 0.8959 |
+| 0.1462        | 10.0  | 240  | 0.3660          | 0.8991   | 0.8990    | 0.8942 | 0.8959 |
 
 
 ### Framework versions

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training_args.bin

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